Method for generating surgical simulation information and program

ABSTRACT

A method for creating surgical simulation information by a computer includes creating a virtual body model corresponding to a body state of a patient for surgery, simulating a specific surgical process on the virtual body model to obtain virtual surgical data, dividing the virtual surgical data into minimum surgical operation units, each unit representing one specific operation, and creating cue sheet data composed of the minimum surgical operation units, wherein the cue sheet data represents the specific surgical process.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of International PatentApplication No. PCT/KR2018/013947, filed on Nov. 15, 2018, which isbased upon and claims the benefit of priority to Korean PatentApplication No. 10-2017-0182888, filed on Dec. 28, 2017. The disclosuresof the above-listed applications are hereby incorporated by referenceherein in their entirety.

BACKGROUND

Embodiments of the inventive concept described herein relate to a methodand a program for creating surgical simulation information.

There is a need to develop a scheme capable of providing information toassist a surgeon in a surgical process. In order to provide theinformation to assist with the surgery, actions of the surgery must berecognized.

Conventionally, in order to design a scenario for optimizing thesurgical process, a medical image that is previously captured isreferred to or an advice from a highly skilled surgeon is referred.However, it is difficult to determine unnecessary processes only basedon the medical image, and the advice of the experienced surgeon is notcustomized to a specific patient.

Therefore, the medical image or the advice of the skilled surgeon maynot be utilized as auxiliary means for optimizing the surgical processfor a surgery target patient as a surgery target.

Accordingly, development of a method for minimizing unnecessaryprocesses in performing the surgery using a 3D medical image (forexample, virtual images of 3D surgical tool movements and internal organchanges caused by the movement of the tool) to optimize the surgicalprocess, and providing surgery assisting information based on theoptimized surgical process is required.

Further, recently, deep learning has been widely used for analysis ofmedical images. Deep learning is defined as a set of machine-learningalgorithms that attempt high-level abstractions (abstracting of keycontent or functions in a large amount of data or complex data) via acombination of several nonlinear transformation schemes. Deep learningmay be largely considered as a field of machine learning that teaches ahuman mindset to a computer.

SUMMARY

Embodiments of the inventive concept provide a method and a program forcreating surgical simulation information.

Purposes that the inventive concept intends to achieve are not limitedto those mentioned above. Other purposes as not mentioned will beclearly understood by those skilled in the art from followingdescriptions.

According to an exemplary embodiment, a method for creating surgicalsimulation information by a computer includes creating a virtual bodymodel corresponding to a body state of a patient for surgery, simulatinga specific surgical process on the virtual body model to obtain virtualsurgical data, dividing the virtual surgical data into minimum surgicaloperation units, each unit representing one specific operation, andcreating cue sheet data composed of the minimum surgical operationunits, wherein the cue sheet data represents the specific surgicalprocess.

Further, the dividing of the virtual surgical data into the minimumsurgical operation units may include recognizing whether a specificevent has occurred based on the virtual surgical data, and recognizingthe minimum surgical operation units based on the specific event,wherein the specific event includes change in at least one of surgicaltool and a surgery target portion included in the virtual surgical data.

Further, the recognizing of whether the specific event has occurred mayinclude recognizing whether the event has occurred, based on change inan operation of the surgical tool, recognizing whether the event hasoccurred, based on change in a state of the surgery target portion, orrecognizing whether the event has occurred, based on whether change in astate of the surgery target portion occurs as change in an operation ofthe surgical tool occurs.

Further, the creating of the cue sheet data may include sequentiallycombining the minimum surgical operation units in a corresponding mannerto the specific surgical process, thereby to create the cue sheet data.

Further, the creating of the virtual body model may include obtaining amedical image including a surgery target portion of the patient, and3D-modeling the obtained medical image to create the virtual body model.

Further, the creating of the virtual body model may further includeobtaining an actual surgery posture of the patient, and 3D-modeling thevirtual body model by correcting the medical image based on the actualsurgery posture.

Further, the method may further include determining whether the createdcue sheet data is optimized.

Further, the determining of whether the created cue sheet data isoptimized may further include providing surgical guide data based on thecue sheet data determined to be optimized.

Further, the determining of whether the created cue sheet data isoptimized may include obtaining optimized cue sheet data, and comparingthe created cue sheet data with the optimized cue sheet data.

Further, the obtaining of the optimized cue sheet data may includeobtaining one or more to-be-learned cue sheet data, performingreinforcement learning using the one or more to-be-learned cue sheetdata, and obtaining the optimized cue sheet data based on thereinforcement learning result.

According to an exemplary embodiment, a computer program is stored in acomputer-readable storage medium, wherein the computer program isconfigured to perform the method as defined above in combination with acomputer as hardware.

According to an exemplary embodiment, a device includes a memory forstoring one or more instructions, and a processor configured to executethe one or more instructions stored in the memory, wherein the processorexecutes the one or more instructions to create a virtual body modelcorresponding to a body state of a patient for surgery, simulate aspecific surgical process on the virtual body model to obtain virtualsurgical data, divide the virtual surgical data into minimum surgicaloperation units, each unit representing one specific operation, andcreate cue sheet data composed of the minimum surgical operation units,wherein the cue sheet data represents the specific surgical process.

BRIEF DESCRIPTION OF THE FIGURES

The above and other objects and features will become apparent from thefollowing description with reference to the following figures, whereinlike reference numerals refer to like parts throughout the variousfigures unless otherwise specified, and wherein:

FIG. 1 is a view showing a robot-based surgery system according to adisclosed embodiment;

FIG. 2 is a flowchart showing a method for creating surgical simulationinformation according to one embodiment;

FIG. 3 is a flowchart showing a 3D modeled data creation process viaapplication of a surgery posture according to one embodiment;

FIG. 4 is a flowchart showing a method for creating surgical simulationinformation according to another embodiment;

FIG. 5 is a flowchart showing a surgical process optimizing methodaccording to one embodiment; and

FIG. 6 is a diagram schematically showing a configuration of a devicefor performing a surgical simulation information creation methodaccording to one embodiment of the inventive concept.

DETAILED DESCRIPTION

Advantages and features of the inventive concept, and methods ofachieving them will become apparent with reference to embodimentsdescribed below in detail in conjunction with the accompanying drawings.However, the inventive concept is not limited to the embodimentsdisclosed below, but may be implemented in various forms. The presentembodiments are provided to merely complete the disclosure of theinventive concept, and to inform merely fully those skilled in the artof the inventive concept of the scope of the inventive concept. Theinventive concept is only defined by the scope of the claims.

The terminology used herein is for the purpose of describing theembodiments only and is not intended to limit the inventive concept. Asused herein, the singular forms “a” and “an” are intended to include theplural forms as well, unless the context clearly indicates otherwise. Itwill be further understood that the terms “comprises”, “comprising”,“includes”, and “including” when used in this specification, specify thepresence of the stated features, integers, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, operations, elements, components, and/orportions thereof. Like reference numerals refer to like elementsthroughout the disclosure. As used herein, the term “and/or” includesany and all combinations of one or more of the associated listed items.Although terms “first”, “second”, etc. are used to describe variouscomponents, it goes without saying that the components are not limitedby these terms. These terms are only used to distinguish one componentfrom another component. Therefore, it goes without saying that a firstcomponent as mentioned below may be a second component within atechnical idea of the inventive concept.

Unless otherwise defined, all terms including technical and scientificterms used herein have the same meaning as commonly understood by one ofordinary skill in the art to which this inventive concept belongs. Itwill be further understood that terms, such as those defined in commonlyused dictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art andwill not be interpreted in an idealized or overly formal sense unlessexpressly so defined herein.

A term “unit” or “module” used herein means software or a hardwarecomponent such as FPGA, or ASIC. The “unit” or “module” performs apredetermined role. However, the “unit” or “module” is not meant to belimited to the software or the hardware. The “unit” or “module” may beconfigured to reside in an addressable storage medium and may beconfigured to execute one or more processors. Thus, in an example, the“unit” or “module” includes components such as software components,object-oriented software components, class components and taskcomponents, processes, functions, attributes, procedures, subroutines,segments of a program code, drivers, firmware, a microcode, circuitry,data, database, data structures, tables, arrays and variables.Functionality provided within the components and the “units” or“modules” may be combined into a smaller number of components and“units” or “modules” or may be further divided into additionalcomponents and “units” or “modules”.

As used herein, a term “image” refers to multi-dimensional data composedof discrete image elements (e.g., pixels in a 2D image and voxels in a3D image). For example, the image may include a medical image of anobject obtained by a CT imaging apparatus.

As used herein, the term “object” may be a person or an animal, or aportion or an entirety of a person or animal. For example, the objectmay include at least one of organs such as a liver, a heart, a uterus, abrain, a breast, and an abdomen, and a blood vessel.

As used herein, a term “user” may be a surgeon, a nurse, a clinicalpathologist, a medical image expert, etc. as a medical expert, may be atechnician repairing a medical apparatus. However, the presentdisclosure is not limited thereto.

As used herein, a term “medical image data” refers to a medical imagethat is captured by a medical imaging apparatus, and includes allmedical images that may represent a body of an object in a 3D modellingmanner The “medical image data” may include a computed tomography (CT)image, a magnetic resonance imaging (MRI) image, a positron emissiontomography (PET) image, etc.

As used herein, a term “virtual body model” refers to a model created ina conforming manner to an actual patient's body based on the medicalimage data. The “virtual body model” may be created by modeling themedical image data in a three dimensions manner or by correcting themodeled data to be adapted to an actual surgery situation.

As used herein, a term “virtual surgical data” means data includingrehearsal or simulation action performed on the virtual body model. The“virtual surgical data” may be image data of rehearsal or simulationperformed on the virtual body model in a virtual space or may be data inwhich a surgical operation performed on the virtual body model isrecorded.

As used herein, a term “actual surgery data” refers to data obtained asa medical staff performs actual surgery. The “actual surgery data” maybe image data obtained by imaging a surgery target portion in an actualsurgical process, or may be data in which a surgical operation performedin the actual surgical process is recorded.

As used herein, a term “detailed surgical operation” means a minimumunit of a surgical operation as divided according to specific criteria.

As used herein, a term “cue sheet data” refers to data in which detailedsurgical operations into which a specific surgical process is dividedare recorded in order.

As used herein, a term “to-be-executed cue sheet data” refers to cuesheet data obtained based on the virtual surgical data obtained viasimulation by the user.

As used herein, a term “training virtual surgical cue sheet data” isincluded in the to-be-executed cue sheet data, and means cue sheet datacreated based on the virtual surgical data obtained via surgerysimulation by the user.

As used herein, a term “referenced virtual surgical cue sheet data”refers to cue sheet data about virtual surgery performed by a specificmedical person for construction of to-be-learned big data or surgeryprocess guidance.

As used herein, a term “optimized cue sheet data” means cue sheet dataabout an optimized surgical process in terms of a surgery time orprognosis.

As used herein, a term “to-be-learned cue sheet data” means cue sheetdata used for learning for optimized cue sheet data calculation.

As used herein, a term “surgery guide data” means data used as guideinformation during actual surgery.

As used herein, a term “computer” includes all of various devicescapable of performing computation and providing the computation resultto the user. For example, the computer may include not only a desktop(PC) and a notebook, but also a smart phone, a tablet PC, a cellularphone, a PCS (Personal Communication Service) phone, a mobile terminalof synchronous/asynchronous IMT-2000 (International MobileTelecommunication-2000), a palm personal computer (PC), and a personaldigital assistant (PDA). Further, when a head mounted display (HMD)apparatus includes a computing function, the HMD apparatus may be acomputer. Further, the computer may be a server that receives a requestfrom a client and performs information processing.

Hereinafter, embodiments of the inventive concept will be described indetail with reference to the accompanying drawings.

FIG. 1 is a view showing a robot-based surgery system according to adisclosed embodiment.

Referring to FIG. 1, a schematic diagram of the system capable ofperforming robot-based surgery according to the disclosed embodiment isillustrated.

According to FIG. 1, the robot-based surgery system includes a medicalimaging apparatus 10, a server 20, and a controller 30, an imaging unit36, a display 32, and a surgery robot 34 provided in an operating room.

In one embodiment, the robot-based surgery may be performed by the usercontrolling the surgery robot 34 using the controller 30. In oneembodiment, the robot-based surgery may be performed automatically bythe controller 30 without the user control.

The server 20 is a computing device including at least one processor anda communication unit.

The controller 30 includes a computing device including at least oneprocessor and a communication unit. In one embodiment, the controller 30includes hardware and software interfaces for controlling the surgeryrobot 34.

The imaging unit 36 includes at least one image sensor. That is, theimaging unit 36 includes at least one camera to image a surgery targetportion. In one embodiment, the imaging unit 36 is used in conjunctionwith the surgery robot 34. For example, the imaging unit 36 may includeat least one camera coupled with a surgery arm of the surgery robot 34.

In one embodiment, the image captured by the imaging unit 36 isdisplayed on the display 32.

The controller 30 receives information necessary for surgery from theserver 20 or creates information necessary for surgery and provides theinformation to the user. For example, the controller 30 displays thecreated or received information necessary for the surgery on the display32.

For example, the user controls movement of the surgery robot 34 bymanipulating the controller 30 while looking at the display 32 toperform robot-based surgery.

The server 20 creates information necessary for robot-based surgeryusing medical image data of the object (patient) previously imaged bythe medical imaging apparatus 10 and provides the created information tothe controller 30.

The controller 30 may display the information received from the server20 on the display 32 to present the information to the user, or may usethe information received from the server 20 to control the surgery robot34.

In one embodiment, imaging means that may be used in the medical imagingapparatus 10 is not limited particularly. For example, various medicalimaging means such as CT, X-Ray, PET, and MRI may be used.

Hereinafter, a method for creating surgical simulation information willbe described in detail with reference to the drawings.

FIG. 2 is a flowchart showing a method for creating surgical simulationinformation according to one embodiment.

Steps shown in FIG. 2 may be performed in time series by the server 20or the controller 30 shown in FIG. 1, or may be performed in a computingdevice provided separately. Hereinafter, for convenience of description,each step is described as being performed by a computer, but a subjectto perform each step is not limited to a specific device. All or some ofthe steps may be performed by the server 20 or the controller 30 or maybe performed by a separate computing device.

Referring to FIG. 2, the surgical simulation information creation methodaccording to an embodiment of the inventive concept may include creatinga virtual body model corresponding to a patient's body state duringsurgery (S200); simulating a specific surgical process for the virtualbody model to acquire virtual surgical data (S400); dividing the virtualsurgical data into minimum surgical operation units, each unitrepresenting one specific operation (S600); and creating a cue sheetdata composed of the minimum surgical operation units to indicate thespecific surgical process (S800). Hereinafter, detailed description ofeach step is as follows.

A computer creates the virtual body model corresponding to the bodystate of the object (e.g., the patient) during surgery (S200).

In one embodiment, the computer may acquire a medical image including asurgery target portion of the object (e.g., the patient), and may createthe virtual body model of the patient by 3D-modeling the acquiredmedical image.

In order for the user to perform a simulation similar to actual surgery,the 3D modeled data corresponding to the actual physical state of thepatient is required.

Conventionally, as medical imaging is performed in a different posturefrom an actual surgery posture and thus-obtained medical image data isdirectly 3D-modeled, the simulation before the actual surgery may notproperly provide an effect of practicing the actual surgery in advance.

Specifically, in general, an internal organ orientation or an organshape in an image of the patient captured by the medical imagingapparatus while the patient lies down is different from an internalorgan orientation or an organ shape of the object during the actualsurgery, due to influence of gravity depending on an angle at which theobject lies down. Thus, the same simulation situation as the actualsurgery may not be provided.

Further, because a pre-surgery simulation is performed in a state inwhich a simulation state of the body is inconsistent with apneumoperitoneum state in which the body is filled with carbon dioxidefor laparoscopic surgery or robot-based surgery, the pre-surgerysimulation may not properly provide an effect of practicing actualsurgery in advance. To solve this problem, it is necessary to create 3Dmodeled data (i.e., 3D pneumoperitoneum model) corresponding to theactual surgical state.

FIG. 3 is a flowchart showing a 3D modeled data creation process viaapplication of a surgery posture according to one embodiment.

As one embodiment, as shown in FIG. 3, the computer creates the 3Dmodeled data based on medical image data captured while applying anactual surgery posture. Specifically, the process may includecalculating, by the computer, a posture of the patient at which thepatient is imaged, based on a surgery posture determined based on thepatient's lesion location or surgery type (S202); and performing, by thecomputer, 3D modeling of medical image data imaged at the calculatedposture (S204).

The computer calculates the posture of the patient at which the patientis imaged, based on the surgery posture determined based on thepatient's lesion location or surgery type (S202). The surgery posturemay vary depending on the patient's lesion location (i.e., a surgicalsite), the type of surgery thereof, and the like. The computercalculates the posture for medical imaging to be identical with thepatient's surgery posture.

For example, when an upper body of the patient is subjected to surgerywhile the patient's body is inclined at 15 degrees, the computer maycalculate, as the posture for imaging, a posture at which the patient'sback is supported on a support such that only the upper body thereof isinclined at 15 degrees. When the posture for imaging is set to theposture at which only the upper body thereof is inclined at 15 degrees,a surgery target portion may be imaged at a posture identical with asurgery posture during actual surgery using the medical imagingapparatus (e.g., a CT apparatus).

Further, for example, the medical imaging apparatus may include afunction of adjusting an orientation of the patient body to implementthe posture for imaging identical with the surgery posture. For example,when the medical imaging apparatus is the computed tomography (CT)apparatus, a table of the CT apparatus may be tilted or rotated by apredetermined angle in a predetermined direction, and a gantry thereofmay be inclined by a predetermined angle in a predetermined direction.

Thus, the computer or the user may control the table and the gantry ofthe medical imaging apparatus to be tilted at an angle corresponding tothe surgery posture. The computer may acquire, from the medical imagingapparatus, the medical image data captured at the posture for imaging atwhich the body is inclined at an angle equal to a an inclination duringthe actual surgery.

Further, the computer may receive the patient's surgery posture from themedical staff, and may directly calculate the surgery posture at whichthe surgery is performed based on the patient's lesion location, thetype of surgery thereof, and the like.

Then, the computer acquires the 3D modeled data as created based on themedical image data imaged at the posture for imaging (S204). Thecomputer may create the 3D modeled data by 3D-rendering the 3D medicalimage of the object. Further, the computer may receive the 3D modeleddata created based on the image captured at a specific posture by themedical imaging apparatus. That is, the medical imaging apparatus (e.g.,the CT apparatus) may perform 3D rendering of the medical image data,create the 3D modeled data, and transmit the created data to thecomputer.

Further, in another embodiment, the computer may apply a correctionalgorithm that changes medical image data imaged under a general imagingcondition to image data corresponding to a body state for a specificsurgery to create the 3D modeled data. That is, the computer may apply abody change according to gravity in the tilted state or a body changedue to the pneumoperitoneum model resulting from carbon dioxideinjection to the medical image data obtained by imaging the patientlying down in a general state, thereby to create the 3D modeled data.

For example, the correction algorithm may be calculated by learning bigdata created by matching medical image data at a general imagingcondition and general body state with body condition data correspondingto surgery at a specific body state and a specific surgery condition.The body state data corresponding to the surgery may include image dataimaging an internal organ shape or orientation during actual surgery orimage data imaging a body surface for actual surgery.

In one embodiment, when creating a pneumoperitoneum model duringlaparoscopic surgery or robot-based surgery based on the medical imagedata (e.g., CT data) imaged under the general condition, the computermay match the patient's medical image data with the body surface datafor the actual surgery and construct big data to be learned based on thematching result. The body surface data may be data imaged by a medicalstaff before the surgery.

For example, the medical staff acquires the body surface data by imagingan abdominal surface deformed by injecting carbon dioxide beforeperforming laparoscopic surgery or robot-based surgery. The computer maylearn the big data to create a correction criterion or a correctionalgorithm to correct 3D modeled data in a general state intopneumoperitoneum model data for laparoscopic surgery or robot-basedsurgery. Thereafter, when medical image data of a new patient isobtained, the computer may correct the 3D modeled data created based onthe medical image data based on the correction criterion or thecorrection algorithm, thereby to create the pneumoperitoneum model data.

Thus, the computer may create the 3D modeled data corresponding to thebody state for surgery of a specific patient and may provide the createddata to the user.

Referring back to FIG. 2, the computer obtains the virtual surgical databy simulating a specific surgical process for the 3D modeled virtualbody model (S400). The user performs a simulation or rehearsal toperform virtual surgery on the 3D modeled image (i.e., virtual bodymodel). For example, the computer may display virtual surgical tool onthe 3D modeled image. The user may control the virtual surgical tool invarious ways to perform rehearsal to perform surgery on the 3D modeledimage.

The virtual surgical data is created by the user simulating surgery onthe 3D modeled virtual body model of the patient. The process ofacquiring the virtual surgical data may be a process in which the usersimulates surgery or in which the user performs rehearsal under the samecondition immediately before the actual surgery. The computer mayreceive the virtual surgical data from the user in various ways.

In one embodiment, the computer may provide the virtual body model tothe user through a virtual reality (VR) device, and may input thesurgical operation for the virtual body model through the controller.The controller may be implemented in various forms to recognize movementof the user's hand. For example, as the controller is embodied in aglove-like shape, detailed finger movement of the user during thesurgery and real-time orientation of a hand thereof may be obtained.

Specifically, the computer provides the virtual body model to a HMDapparatus worn by the user. The computer rotates or enlarges the virtualbody model according to the user's manipulation and provides the rotatedor enlarged virtual body model to the user. Accordingly, the userperforms surgery planning and simulation while examining in detail thevirtual body model implemented in the same way as that a body model forthe actual surgery scheduled for the patient.

For example, blood vessels and organs that are to be subjected to actualsurgery may not be visible to the user due to fat such as omentum(serous membrane), depending on body characteristics of the object. Inmodeling, the omentum may be removed such that the user may accuratelyknow a location and a shape of the actual blood vessel and organ.Accordingly, the user may establish an optimal surgery plan to reach asurgery target portion for the actual surgery. The computer acquires aninput that specific surgical tool is selected by the user, and acquires,through the controller, user manipulation to perform surgery on aspecific area of the virtual body model using the corresponding surgicaltool.

Further, in one embodiment, the virtual surgical data may include imagedata imaging implementation of a surgical operation performed by theuser on the virtual body model. The computer may create a simulationimage based on real-time motion data acquired by the controller, thesurgical tool having the motion, and a position in the virtual bodymodel to which the tool moves via the motion.

Further, in another embodiment, the virtual surgical data may bemodeling data for the virtual body model itself, and a collection ofsurgical tool and motion data used at each time in a simulation orrehearsal process. That is, the virtual surgical data may be a pluralityof data sets that an external computer may receive and which may allowimplementing a simulation image.

The computer divides the virtual surgical data into minimum surgicaloperation units, each unit representing one specific operation (S600).

The surgery process refers to a process in which a series of surgicaloperations are performed on the surgery target portion using thesurgical tool. Therefore, the virtual surgical data obtained bysimulating a specific surgical process includes a series of surgicaloperations.

That is, the computer may divide the virtual surgical data including aseries of surgical operations into the minimum surgical operation units,the minimum unit meaning one specific operation. In this connection, theminimum surgical operation unit refers to a minimum operation unit thatmay be expressed as a specific surgical operation among a series ofsurgical operations constituting the entire surgical process. That is,the minimum surgical operation unit may be a detailed surgical operationrepresenting one specific surgical operation.

In this connection, one specific detailed surgical operation may becomposed of consecutive operations having the same pattern for thesurgical tool or the surgery target portion. In other words, when thevirtual surgical data includes a first detailed surgical operation and asecond detailed surgical operation, the first detailed surgicaloperation and the second detailed surgical operation may have differentoperation patterns. Accordingly, the computer may recognize a time pointcorresponding to information different from information corresponding toa current time point based on information corresponding to each of timepoints of the virtual surgical data, and determine whether an operationpattern at the recognized time point is different from that of adetailed surgical operation at the current time point.

In one embodiment, the computer may recognize whether a specific eventoccurs based on the virtual surgical data, and may recognize the minimumsurgical operation unit based on the recognized specific event and thusmay divide the virtual surgical data into at least one minimum surgicaloperation unit.

For example, the computer may recognize change in the surgical tool orthe surgery target portion (e.g., an organ such as a liver, a stomach, ablood vessel, a tissue, etc.) based on information included in thevirtual surgical data at each time point of the virtual surgical data,and may determine whether an event occurs based on the change. That is,the computer may recognize whether an event occurs based on operationchange of the surgical tool, recognize whether an event occurs based onstate change of the surgery target portion, or recognize whether anevent occurs based on whether change state of the surgery target portionoccurs as the operation change of the surgical tool occurs.

For example, the computer may recognize whether an event has occurredbased on change in a position, an orientation, a movement degree, atype, etc. of the surgical tool. Upon the determination that the eventhas occurred, the computer may determine whether operations as performedby the surgical tool at before and after an event occurrence time aredifferent from each other. When the operations as performed by thesurgical tool at before and after the event occurrence time aredifferent from each other, each of the operation before the eventoccurrence time and the operation after the event occurrence time mayconstitute each detailed surgical operation as the minimum surgicaloperation unit.

Alternatively, the computer may recognize whether an event has occurredbased on change in a position, an orientation, a state, etc. of thesurgery target portion. Upon the determination that the event hasoccurred, the computer may determine whether the surgery target portionsbefore and after an event occurrence time are different from each other.If so, each of an operation before the event occurrence time and anoperation after the event occurrence time may constitute each detailedsurgical operation as the minimum surgical operation unit.

Alternatively, the computer may recognize whether an event has occurredbased on whether the surgical tool contacts the surgery target portionor change in the surgery target portion due to presence or absence ofenergy of the surgical tool occurs. Upon the determination that theevent has occurred, the computer may determine whether surgery operationpatterns before and after an event occurrence time are different fromeach other. If so, each of an operation before the event occurrence timeand an operation after the event occurrence time may constitute eachdetailed surgical operation as the minimum surgical operation unit.

Alternatively, the computer may recognize whether an event has occurredbased on whether bleeding has occurred in the surgery target portion.Upon the determination that the event has occurred, the computer maydetermine whether surgery operation patterns before and after an eventoccurrence time are different from each other. If so, each of anoperation before the event occurrence time and an operation after theevent occurrence time may constitute each detailed surgical operation asthe minimum surgical operation unit.

Further, according to an embodiment of the inventive concept, thevirtual surgical data may be divided to the detailed surgical operations(that is, a minimum surgical operation units) based on whether the eventoccurs, as described above. However, the present disclosure is notlimited thereto. The virtual surgical data may be divided to thedetailed surgical operations (that is, a minimum surgical operationunits) based on many other criteria.

For example, the virtual surgical data may be divided to the detailedsurgical operations based on surgery types (e.g., laparoscopic surgery,robot-based surgery), anatomical body parts where surgery is performed,surgical tools as used, a number of surgical tools, an orientation or aposition of the tool displayed on a screen, movement of the surgicaltool (for example, forward/reward movement), etc.

The division criteria and detailed categories included within thedivision criteria may be directly set by the medical staff learning theactual surgery data. The computer may perform supervised learning basedon the division criteria and the detailed categories set by the medicalstaff to divide the virtual surgical data into the detailed surgicaloperations as a minimum operation unit.

Further, the division criteria and detailed categories included withinthe division criteria may be extracted via learning of a surgical imageby the computer. For example, the computer may calculate the divisioncriteria and detailed categories included within the division criteriavia deep learning (i.e., unsupervised learning) of actual surgery dataaccumulated as big data. Subsequently, the computer may divide thevirtual surgical data based on the division criteria created via thelearning of the actual surgery data to create the cue sheet data.

Further, in another embodiment, the virtual surgical data or actualsurgery data may be divided based on a result of determining whether thevirtual surgical data or actual surgery data satisfies the divisioncriterion via image recognition. That is, the computer may recognize theanatomical organ position on the screen, the number of surgical toolsappearing on the screen, and the number of the surgical tools on thescreen within the image of the virtual surgical data or actual surgerydata as the division criterion and may divide the virtual surgical dataor actual surgery data into the detailed surgical operation units basedon the recognized division criterion.

Further, in another embodiment, the computer may perform the divisionprocess for cue sheet data creation based on surgical tool movement dataincluded in the actual surgery data or the virtual surgical data. Theactual surgery data may include various information input in a processof controlling the surgery robot, such as the type and the number ofsurgical tools selected by the user, information about the movement ofeach surgical tool when the user performs robot-based surgery. Thevirtual surgical data may include information on the type and the numberof surgical tools selected by the user, and movement of each surgicaltool during the simulation of the virtual body model. Accordingly, thecomputer may perform division based on information included in theactual surgical data or virtual surgical data at each time pointthereof.

Further, in one embodiment, the virtual surgical data or actual surgerydata includes various types of actions such as ablation and suture.Division is performed based on the division criteria. Specifically, aprocess of dividing the actual surgical data (for example, actualsurgery image) about the actual gastric cancer surgery or the virtualsurgical data about the simulation of the gastric cancer surgery intodetailed surgical operations to create the cue sheet data is as follows.

For example, gastric cancer surgery includes an action to ablate aportion or an entirety of a stomach containing a tumor, and an action toablate a lymph node. In addition, various resections and connections areused depending on a state of the gastric cancer. In addition, eachaction may be divided into a plurality of detailed actions based on aspecific location where the action is taken and a direction of movementof the surgical tool.

For example, the detailed operation of the gastric cancer surgery may bedivided into an opening step, an ablation step, a connection step, and asuture step.

Further, a method of changing a disconnected state of an organ to aconnected state includes an in vitro anastomosis method of incising andconnecting at least 4 to 5 cm of an end of an anticardium, and an invivo anastomosis method in which about 3 cm of umbilicus is incised andincision and anastomosis occur in an abdominal cavity. Theabove-described connection step may be divided in detailed sub-stepsaccording to the specific connection method as described above.

Furthermore, each surgery operation may be divided into a plurality ofdetailed surgical operations according to the position and the movementof the surgical tool.

The computer creates the cue sheet data composed of minimum surgicaloperation units (i.e., detailed surgical operations) and representing aspecific surgical process (S800). That is, the computer may sequentiallycombine the at least one minimum surgical operation unit in acorresponding manner to the specific surgical process simulated usingthe virtual body model to create the cue sheet data.

According to one embodiment of the inventive concept, each of thedivided detailed surgical operations (i e , minimum surgical operationunits) has a standardized name allocated thereto based on a locationwhere the detailed surgical operation is performed and a pathway of thesurgical tool.

In one embodiment, the standardized name may be variously defined. Forexample, when dealing with a specific portion as a lower right portionof the stomach, the name of the portion may be a name commonly used inthe medical field. More comprehensive or detailed names defined in thesystem according to the disclosed embodiment may be used.

Therefore, the rehearsal image may be organized into information in aform of a cue sheet in which a plurality of actions are sequentiallyarranged based on the standardized names. Similarly, the surgery imageabout the surgery performed by the user may be divided into actionunits, and may be organized into cue sheet information.

Further, in one embodiment, the cue sheet data may be created as codedata of specific digits based on the division criteria for dividing thesurgical data into the detailed surgical operations. That is, thecomputer divides the virtual surgical data into standardized detailedsurgical operations by applying standardized division criteria anddesignating detailed categories within the division criteria. Thecomputer may allocate a standardized code value to each detailedcategory and allocate standardized code data to distinguish eachdetailed surgical operation.

The computer allocates, to each detailed surgical operation, digitalizedcode data obtained by allocating numbers or letters to categories inorder from a higher category to a lower category to which the specificdetailed surgical operations belong, according to the order ofapplication of the division criteria. Thus, the computer may create cuesheet data in a form in which not images of the divided detailedsurgical operations but the standardized code data of the detailedsurgical operations are listed. Further, the user may share or deliverthe simulated surgical process by providing only the cue sheet datacomposed of the standardized code data.

Further, in one embodiment, the computer may allocate a standardizedname to a standardized code of each detailed surgical operation. Thus,the user may select and identify only a desired surgical operation (oraction) within the entire cue sheet. Further, in this case, the user mayeasily grasp a progress of the surgery or the rehearsal by simplyviewing the cue sheet in which actions are sequentially arranged basedon the standardized names thereof, without viewing an entirety of therehearsal or surgery image.

The cue sheet data may be converted into a surgical image using an imagedatabase for each detailed surgical operation. In the image data base,an image matching each code data may be stored. A plurality of imagesmatching each code data may be stored therein depending on a situation.For example, specific detailed code data may include different detailedsurgical operation images in the image database according to previouslyperformed operations.

Further, as each cue sheet data is matched with a specific virtual bodymodel and the matching result is stored, the computer may reproduce thecue sheet data as a surgical simulation image by sequentially applyingthe detailed surgical operations included in the cue sheet data to thevirtual body model.

Therefore, the image corresponding to the cue sheet may be reproduced inthe same point of view as that of the surgery rehearsal image.Alternatively, the image corresponding to the cue sheet may bereconstructed in a point of view different from that of the surgeryrehearsal image and the reconstructed image may be reproduced.Alternatively, the image may be modeled in a 3D manner, and thus theviewpoint and a position thereof may be adjusted according to the user'smanipulation.

Further, as shown in FIG. 4, in another embodiment, the method mayfurther include determining, by the computer, whether to-be-executed cuesheet data as created based on the user's virtual surgical data isoptimized (S1000).

The computer determines adequacy of the to-be-executed cue sheet datavia comparison between the to-be-executed cue sheet data and optimizedcue sheet data. For example, the computer may determine whether anunnecessary detailed surgical operation that delays a surgery time iscontained in the to-be-executed cue sheet data created based on thesimulation result by the user, and whether a detailed surgical operationthat must be contained before or after a specific detailed surgicaloperation when performing the specific detailed surgical operation isabsent in the to-be-executed cue sheet data. Thus, the computer maydetermine whether the to-be-executed cue sheet data has been created ina proper manner to be applied to actual surgery of the patient.

The computer may perform a process of calculating optimized cue sheetdata to perform evaluation of the to-be-executed cue sheet data.

FIG. 5 is a flowchart showing a surgical process optimizing methodaccording to one embodiment.

The computer acquires one or more to-be-learned cue sheet data (S1020).The to-be-learned cue sheet data refers to learning target data that isto be learned for calculation of the optimized cue sheet data. Theto-be-learned cue sheet data may include cue sheet data created based onthe actual surgery data (i.e. actual surgery cue sheet data) or cuesheet data created based on the simulated virtual surgical data forreference (i.e. referenced virtual surgery cue sheet data). The actualsurgery cue sheet data is created by the computer dividing the actualsurgery data according to the division criteria. The referenced virtualsurgical cue sheet data is not obtained in the user's surgery simulationprocess, but is created by performing simulation for purpose ofconstructing the learning target data or providing the same topractitioners for reference.

Thereafter, the computer performs reinforcement learning using theto-be-learned cue sheet data (S1040). The reinforcement learning refersto one area of the machine learning, and refers to a method in which anagent defined in a certain environment recognizes a current state andselects an action or a sequence of actions that maximizes reward amongselectable actions or sequences thereof. The reinforcement learning maybe summarized as learning of a scheme of maximizing compensation basedon state transition and compensation according to the state transition.

Then, the computer calculates the optimized cue sheet data using thereinforcement learning result (S1060). The optimized cue sheet data iscalculated based on the shortest surgical time that may reduce thepatient's anesthesia time, a minimum bleeding amount, an essentialoperation group, and an essential performance sequence, etc. based onthe reinforcement learning result.

The essential operation group refers to a group of detailed surgicaloperations that must be performed together to perform a specificdetailed surgical operation. The essential performance sequence refersto a surgical operation sequence at which that operations must besequentially performed in a course of performing specific surgery. Forexample, surgical operations that must be performed sequentially and anorder thereof may be determined according to the type of surgery or thetype of the surgical operation.

Further, the computer may calculate situation-based optimized cue sheetdata based on the patient's physical condition, the surgery targetportion (e.g., tumor tissue) condition (e.g., a size, a location, etc.of the tumor) thereof via the reinforcement learning. To this end, thecomputer utilizes the patient condition, the surgery target portioncondition, and the like along with the to-be-learned cue sheet data forlearning.

In one embodiment, the computer may perform virtual simulation surgeryon its own. For example, the computer may create a surgical processaccording to the type of surgery and the type of the patient based onthe disclosed surgical process optimizing method, and may perform thevirtual surgery simulation based on the created surgical process.

The computer evaluates results of the virtual surgery simulation. Thecomputer may perform the reinforcement learning based on virtualsurgical simulation information and evaluation information on the resultthereof, thereby to obtain an optimized surgical process.

A model trained to create the optimal surgical process may not create anoptimized surgical process according to an induvial patient and a typeof surgery thereof because in actual surgery, body structures and typesof surgery of patients are different from each other.

Therefore, the computer may create a surgical process based on thepatient's body structure and the type of surgery thereof using thetrained model, and may perform virtual surgery simulation, based on thecreated surgical process. In this way, the computer may create anoptimized surgical process for an individual patient and a type ofsurgery thereof via the reinforcement learning.

Further, as shown in FIG. 4, in another one embodiment, the method mayfurther include providing, by the computer, surgery guide data based onspecific cue sheet data according to the user's request (S1200). Thatis, the computer may provide the user with the cue sheet data created bythe user performing the simulation or rehearsal during surgery.

FIG. 6 is a diagram schematically showing a configuration of a device200 for performing a surgical simulation information creation methodaccording to one embodiment of the inventive concept.

Referring to FIG. 6, a processor 210 may include one or more cores (notshown), a graphics processing unit (not shown) and/or a connection path(for example, a bus, etc.) for communicating signals with othercomponents.

The processor 210 according to one embodiment performs one or moreinstructions stored in a memory 220 to perform the surgical simulationinformation creation method as described with reference to FIG. 2 toFIG. 5.

In an example, the processor 210 may execute one or more instructionsstored in the memory 220 to create the virtual body model correspondingto the patient's body state for surgery, to obtain the virtual surgicaldata by simulating a specific surgical process for the virtual bodymodel, to divide the virtual surgical data into the minimum surgicaloperation units, each unit representing one specific operation, and tocreate the cue sheet data composed of the minimum surgical operationunits and indicating the specific surgical process.

In one example, the processor 210 may further include RAM (Random AccessMemory) (not shown) and ROM (Read-Only Memory) (not shown) temporarilyand/or permanently storing therein a signal (or data) processed insidethe processor 210. Further, the processor 210 may be implemented in aform of a system on chip (SoC) including at least one of a graphicprocessing unit, RAM, and ROM.

In the memory 220, programs (one or more instructions) for processingand controlling functions by the processor 210 may be stored. Theprograms stored in the memory 220 may be divided into a plurality ofmodules according to functions.

The surgical simulation information creation method according to oneembodiment of the inventive concept as described above may beimplemented using a program (or application) to be executed incombination with a computer as hardware and stored in a medium.

The program may include codes coded in computer languages such as C,C++, JAVA, and machine language that a processor (CPU) of the computermay read through a device interface thereof, in order for the computerto read the program and execute methods implemented using the program.The code may include a functional code related to a function definingfunctions required to execute the methods, and an executionprocedure-related control code necessary for the processor of thecomputer to execute the functions in a predetermined procedure.Moreover, the code may further include a memory reference-related codeindicating a location (address) of an internal memory of the computer oran external memory thereto in which additional information or medianecessary for the processor to execute the functions is stored.Moreover, when the processor of the computer needs to communicate withany other remote computer or server to execute the functions, the codemay further include a communication-related code indicating how tocommunicate with any other remote computer or server using acommunication module of the computer, and indicating information ormedia to be transmitted and received during the communication.

The storage medium means a medium that stores data semi-permanently,rather than a medium for storing data for a short moment, such as aregister, a cache, or a memory, and that may be readable by a machine.Specifically, examples of the storage medium may include, but may not belimited to, ROM, RAM, CD-ROM, a magnetic tape, a floppy disk, and anoptical data storage device. That is, the program may be stored invarious recording media on various servers to which the computer mayaccess or on various recording media on the user's computer. Moreover,the medium may be distributed over a networked computer system so that acomputer readable code may be stored in a distributed scheme.0

The steps of the method or the algorithm described in connection withthe embodiments of the inventive concept may be implemented directly inhardware, a software module executed by hardware, or a combinationthereof. The software modules may reside in random access memory (RAM),read only memory (ROM), erasable programmable ROM (EPROM), electricallyerasable programmable ROM (EEPROM), a flash memory, a hard disk, aremovable disk, CD-ROM, or any form of a computer readable recordingmedium well known in the art.

According to the disclosed embodiments, the surgical simulationinformation optimized for each patient is created using previouslyobtained information and is provided to the surgeon during surgery toassist the surgery.

The effects of the inventive concept are not limited to the effectsmentioned above. Other effects not mentioned will be clearly understoodby those skilled in the art from the above description.

While the inventive concept has been described with reference toexemplary embodiments, it will be apparent to those skilled in the artthat various changes and modifications may be made without departingfrom the spirit and scope of the inventive concept. Therefore, it shouldbe understood that the above embodiments are not limiting, butillustrative.

What is claimed is:
 1. A method for creating surgical simulationinformation by a computer, the method comprising: creating a virtualbody model corresponding to a body state of a patient for surgery;simulating a specific surgical process on the virtual body model toobtain virtual surgical data; dividing the virtual surgical data intominimum surgical operation units, each unit representing one specificoperation; and creating cue sheet data composed of the minimum surgicaloperation units, wherein the cue sheet data represents the specificsurgical process.
 2. The method of claim 1, wherein the dividing of thevirtual surgical data into the minimum surgical operation unitsincludes: recognizing whether a specific event has occurred based on thevirtual surgical data; and recognizing the minimum surgical operationunits based on the specific event, wherein the specific event includeschange in at least one of surgical tool and a surgery target portionincluded in the virtual surgical data.
 3. The method of claim 2, whereinthe recognizing of whether the specific event has occurred includes:recognizing whether the event has occurred, based on change in anoperation of the surgical tool; recognizing whether the event hasoccurred, based on change in a state of the surgery target portion; orrecognizing whether the event has occurred, based on whether change in astate of the surgery target portion occurs as change in an operation ofthe surgical tool occurs.
 4. The method of claim 1, wherein the creatingof the cue sheet data includes sequentially combining the minimumsurgical operation units in a corresponding manner to the specificsurgical process, thereby to create the cue sheet data.
 5. The method ofclaim 1, wherein the creating of the virtual body model includes:obtaining a medical image including a surgery target portion of thepatient; and 3D-modeling the obtained medical image to create thevirtual body model.
 6. The method of claim 5, wherein the creating ofthe virtual body model further includes: obtaining an actual surgeryposture of the patient; and 3D-modeling the virtual body model bycorrecting the medical image based on the actual surgery posture.
 7. Themethod of claim 1, wherein the method further comprises determiningwhether the created cue sheet data is optimized.
 8. The method of claim7, wherein the determining of whether the created cue sheet data isoptimized further includes providing surgical guide data based on thecue sheet data determined to be optimized.
 9. The method of claim 7,wherein the determining of whether the created cue sheet data isoptimized includes: obtaining optimized cue sheet data; and comparingthe created cue sheet data with the optimized cue sheet data.
 10. Themethod of claim 9, wherein the obtaining of the optimized cue sheet dataincludes: obtaining one or more to-be-learned cue sheet data; performingreinforcement learning using the one or more to-be-learned cue sheetdata; and obtaining the optimized cue sheet data based on thereinforcement learning result.
 11. A computer program stored in acomputer-readable storage medium, wherein the computer program isconfigured to perform the method of claim 1 in combination with acomputer as hardware.
 12. A device comprising: a memory for storing oneor more instructions; and a processor configured to execute the one ormore instructions stored in the memory, wherein the processor isconfigured to execute the one or more instructions to: create a virtualbody model corresponding to a body state of a patient for surgery;simulate a specific surgical process on the virtual body model to obtainvirtual surgical data; divide the virtual surgical data into minimumsurgical operation units, each unit representing one specific operation;and create cue sheet data composed of the minimum surgical operationunits, wherein the cue sheet data represents the specific surgicalprocess.